Python Formatter

Normalised the indentation of 4 line(s) of Python at 4-space steps.

How it works

• Detected the smallest original indentation step.
• Mapped each line's original indent level to a consistent 4-space width.
• Left the author's block structure untouched so the code cannot be re-associated.
• Copied triple-quoted strings, comments and bracket-continuation alignment verbatim.

• Because Python is indentation-significant, the formatter preserves every block boundary and never re-blocks code.
• Continuation lines inside brackets keep their original alignment so wrapped expressions stay readable.
• Output is 4 line(s); formatting it again changes nothing.

Methodology

1. Detect the smallest positive indentation step in the source.
2. Map each line's original leading width to a level and re-emit it at level × the chosen indent size.
3. Track triple-quoted strings and bracket depth with a string/comment-aware scanner so those regions are copied verbatim.

Usage

1. Paste or type a Python file.
2. Choose a 2- or 4-space indent.
3. Run the formatter and copy the result.

Examples

These are examples, not current values: they use fixed inputs, while the interactive tool computes live results in your browser.

Nested blocks normalised

{
  "text": "def f():\n  if x:\n      return 1\n  return 0",
  "indentSize": 4
}

Triple-quoted string preserved

{
  "text": "x = \"\"\"\n  keep   me\n\"\"\"",
  "indentSize": 2
}

Tab indentation converted

{
  "text": "def f():\n\treturn 1",
  "indentSize": 4
}

Limitations

Why indentation-only

Python's block structure is encoded in indentation, so a formatter that re-derived blocks from keywords would risk re-associating code. This tool keeps your blocks and normalises their visual width.

The result is consistent indentation that reads the same across editors and diffs.